Use of respiratory signal analysis to assess severity of Brachycephalic Obstructive Airway Syndrome (BOAS) in dogs.

Abstract

Brachycephalic Obstructive Airway Syndrome (BOAS) is a potentially life-threatening condition that can be challenging to diagnose and grade objectively. The aim of this study was to investigate the use of respiratory signal analysis to assess severity of BOAS in dogs. Hundred and seventeen client-owned dogs of brachycephalic and non-brachycephalic breeds were enrolled. Respiratory sounds were recorded using an electronic stethoscope before and after a 3-minute exercise test (ET). Dogs were assigned a BOAS severity grade (BOAS 0-3) using a validated respiratory functional grading scheme. Signal analysis techniques were used to identify seven sound variables. Analysis of variance (ANOVA) was used to investigate associations between variables and BOAS severity and receiver operating characteristic (ROC) curves to assess the diagnostic efficacy of each sound variable. For each sound variable, there was a significant association with BOAS grade. An increase in BOAS grade resulted in greater sound magnitude in the frequency spectrum (0-1000 Hz), and in a greater contribution of lower frequencies (170-260 Hz). The variable "Peak 1" had the best performance in predicting BOAS negative (BOAS 0 +1) versus BOAS positive dogs (BOAS 2 + 3) before the ET; area under the curve (AUC) = 76.6 % (95 % confidence interval 67.4-85.8 %), whereas the variable "Valley 1" had the highest predictive value after the ET; AUC = 87.8 % (95 % confidence interval 81.4-94.3 %). Respiratory signal analysis has good potential for assessing BOAS severity and could be valuable for clinicians in clinical decision processes and for breeders when selecting suitable breeding dogs.